Algorithm 2: FeaturesEnhancement(FeatureMaps): Enhances the features of the given feature maps using a self-attention mechanism
	Input FeatureMaps: The feature maps are extracted from an AlexNet CNN model.
	Output: Enhance the features of the given feature maps using a self-attention mechanism.
Step 1	Extract feature maps using the CNN model: FeatureMaps = Extract-Maps().
Step 2	Compute spatial attention: ComputeSpatialAttention(FeatureMaps): begin.
	Repeat for position in FeatureMaps:
	AttentionScores = SpatialAttentionScores(position)
	WeightedSumFeatures = WeightedSumFeatures(FeatureMaps, AttentionScores, position)
	[End for Loop]
	SpatialAttentionMaps SpatialAttention(FeatureMaps) End function
Step 3	Compute channel attention: ChannelAttention(FeatureMaps): begin.
	Repeat for channel in FeatureMaps:
	AttentionScores = ChannelAttentionScores(channel)
	WeightedChannelFeatures = WeightedChannelFeatures(FeatureMaps, AttentionScores, channel)
	ChannelAttentionFeatureMaps = ChannelAttention(FeatureMaps)
	[End for loop] [end function]
Step 4	CombineAttention(SpatialAttentionFeatureMaps, ChannelAttentionFeatureMaps)
Step 5	EnhancedFeatureMaps = ElementWiseMultiply(SpatialAttentionFeatureMap, ChannelAttentionFeatureMap)
Step 6	EnhancedFeatureMaps = Combine (SpatialAttentionFeatureMaps, ChannelAttentionFeatureMaps)
	[End of Algorithm]